Data analytics has a wide range of applications in computing systems (e.g., from data mining to machine learning and artificial intelligence), and is an increasingly important aspect of many large-scale computing applications. Data discretization is an important preprocessing step for certain data analytics applications, and may involve grouping a collection of values into a smaller number of “bins” that each correspond to a particular data interval or range. It can be challenging, however, to determine an appropriate size for the intervals or “bins” that are used to perform data discretization.